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JMA Data MCP

JMA Data MCP

by koizumikento
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

List Prefectures

list_prefectures
Read-onlyIdempotent

Retrieve all prefecture codes for JMA weather forecasts to select the correct region for data queries.

Instructions

List all available prefecture codes for weather forecast.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_prefectures"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.2.1
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observed

TDQS

A3.7/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered elsewhere. The word 'all' usefully signals a complete, unpaginated enumeration, but nothing else about behavior is added. With an output schema present, return-shape disclosure is not required.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One short sentence with no filler, front-loading the verb and resource. Nothing could be removed without losing meaning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, read-only enumeration with an output schema and full annotation coverage, the description is nearly sufficient. The only real gap is not naming which sibling tools consume the returned codes, which would have made the workflow chain obvious.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The description correctly implies the tool needs no input.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Specific verb ('List') plus resource ('prefecture codes') and a stated purpose ('for weather forecast'). It is clearly distinct from the station- and weather-oriented siblings, though it never explicitly says so.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied by the phrase 'for weather forecast' — an agent can infer this is a lookup to obtain codes used as input elsewhere, but there is no explicit when-to-use statement or reference to the downstream tools that consume these codes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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